Considering patient safety in autonomous e-mental health systems - detecting risk situations and referring patients back to human care

Background: Digital health interventions can fill gaps in mental healthcare provision. However, autonomous e-mental health (AEMH) systems also present challenges for effective risk management. To balance autonomy and safety, AEMH systems need to detect risk situations and act on these appropriately. One option is sending automatic alerts to carers, but such 'auto-referral' could lead to missed cases or false alerts. Requiring users to actively self-refer offers an alternative, but this can also be risky as it relies on their motivation to do so. This study set out with two objectives. Firstly, to develop guidelines for risk detection and auto-referral systems. Secondly, to understand how persuasive techniques, mediated by a virtual agent, can facilitate self-referral. Methods: In a formative phase, interviews with experts, alongside a literature review, were used to develop a risk detection protocol. Two referral protocols were developed - one involving auto-referral, the other motivating users to self-refer. This latter was tested via crowd-sourcing (n = 160). Participants were asked to imagine they had sleeping problems with differing severity and user stance on seeking help. They then chatted with a virtual agent, who either directly facilitated referral, tried to persuade the user, or accepted that they did not want help. After the conversation, participants rated their intention to self-refer, to chat with the agent again, and their feeling of being heard by the agent. Results: Whether the virtual agent facilitated, persuaded or accepted, influenced all of these measures. Users who were initially negative or doubtful about self-referral could be persuaded. For users who were initially positive about seeking human care, this persuasion did not affect their intentions, indicating that a simply facilitating referral without persuasion was sufficient. Conclusion: This paper presents a protocol that elucidates the steps and decisions involved in risk detection, something that is relevant for all types of AEMH systems. In the case of self-referral, our study shows that a virtual agent can increase users' intention to self-refer. Moreover, the strategy of the agent influenced the intentions of the user afterwards. This highlights the importance of a personalised approach to promote the user's access to appropriate care.Interactive Intelligenc

The adaptive capability of the operational team to respond to challenges in the Emergency Centre. A SenseMaker® study in Emergency Centres within Cape Town

Background Emergency centres (ECs) serve as a main entry point for patients into hospitals, and patients that present here are undifferentiated with varying levels of acuity. Uncertainty, interruptions, multiple – often conflicting – priorities, and gaps in information flow are inherent to EC work practices, making it a high-risk environment for operational failure. The EC team, the core of which is formed by doctors and nurses, needs the ability to collaboratively and reliably sense and respond to the constant change and flux of information. This depends on the interactions and sense-making of the EC team. Objectives People give meaning to situations through the process of sense-making; they then subjectively construct their reality and share it via plausible stories regarding their situation and environment. The main objective of this study was to explore the collective team-based sense-making of the operational challenges and decisions within the EC. This interprofessionalstudy focused on the dynamics and negotiations within the EC as a complex adaptive system. Methods This exploratory study used narrative-based inquiry with abductive reasoning to meet the objectives. It was divided into two sections. The first was a thick description of the EC context, daily operations and processes. Then, using the SenseMaker® tool, we captured stories about a situation that stood out to participants, and thus mattered to them. Using this novel method, once they told their story, the storytellers self-analysed their stories within a specially designed framework. The results were then explored to find patterns based on the perspectives of sense-making. Results There is no proof of interprofessional sense-making in the EC, and if it occurs it is due to the informal networks between doctors and nurses, and despite formal structure. There is an operational disconnect between doctors, nurses and management, which is caused by information asymmetry, poor feedback loops and disparate communication channels. Because there is no collective sense-making, the EC team is vulnerable to operational failure and crises. Currently, they respond to operational challenges via quick fixes that result in constant firefighting, the impact of which could be seen by the extensive use of war-related metaphors in their stories

What is the lived experience of Advanced Nurse Practitioners of managing risk and patient safety in acute settings? A phenomenological perspective

Background: Managing clinical risk and patient safety is high on clinical and political agendas. Advanced Nurse Practitioners (ANPs) are frontline practitioners making critical decisions regarding risk and patient safety. Whilst research around nurse decision-making has been conducted, the extent to which ANPs manage and navigate patient safety and risk is under-researched. Research question: What is the lived experience of Advanced Nurse Practitioners of managing risk and patient safety in acute settings? A phenomenological perspective.Method: Ten ANPs across three acute settings were recruited and iterative data collected over ten months on experiences of managing risk and safety (reflective interviews, written reflections, researcher journal). Data analysis was based on Van Manen’s approach, assisted by NVivo 11 to facilitate circles of interpretation with each data source.Findings: In an environment driven by time pressures, how practitioners cope with managing risk and patient safety is dependent on the presenting situation, breadth of knowledge-base, application of evidence, degree of perceived management support, and channelling of emotive moods. In situations of uncertainty, insufficient knowledge, and/or lack of information, practitioners were guided by care, concern, worry, feeling happy or comfortable and, in critical times, fuelled by fear. These were illuminated to be both drivers and barriers to practitioners’ capabilities in grasping patient presentations. Snapshot judgements were individualized and negotiated dependent on practitioners’ and patients’ capacity to cope with risk. Experiences of risk often identified a learning need or knowledge deficit, revealing an opportunity to develop and advance ANP practice.Implications: These findings have implications for the preparation, training, and ongoing educational and emotional support of ANPs within their practice. Recognising the emotional toll of managing risk and providing the necessary support will ultimately positively impact recruitment and retention of these crucial health care professionals

Where has all the psychology gone? A critical review of evidence-based psychological practice in correctional settings

Evidence-Based Practice (EBP) represents the gold standard for effective clinical psychological practice. In this review, we examine ways in which EBP tenets are being neglected by correctional psychologists worldwide. We examine three key aspects of EBP currently being neglected: (a) individualized and flexible client focus, (b) the therapeutic alliance, and (c) psychological expertise. We also highlight two highly related issues responsible for correctional psychologists' neglect of EBP. The first relates to policy makers' and correctional psychologists' overreliance on the Risk–Need–Responsivity Model to guide correctional practice. We argue that the narrow focus and implementation of this model has resulted in a severe identity problem for correctional psychologists that has severely exacerbated the dual relationship problem. That is, the tension psychologists experience as a result of engaging in psychological practice while also obliging the risk and security policies of correctional systems. The second issue concerns psychologists' response to the dual relationship problem. In short, psychology, as a discipline appears to have acquiesced to the dual-relationship problem. In our view, this constitutes a ‘crisis’ for the discipline of correctional psychology. We offer several recommendations for injecting EBP back into correctional psychology for the individual, psychology as a discipline, and correctional policy makers

Developing an eMental health monitoring module for older mourners using fuzzy cognitive maps

Objective: Effective internet interventions often combine online self-help with regular professional guidance. In the absence of regularly scheduled contact with a professional, the internet intervention should refer users to professional human care if their condition deteriorates. The current article presents a monitoring module to recommend proactively seeking offline support in an eMental health service to aid older mourners. Method: The module consists of two components: a user profile that collects relevant information about the user from the application, enabling the second component, a fuzzy cognitive map (FCM) decision-making algorithm that detects risk situations and to recommend the user to seek offline support, whenever advisable. In this article, we show how we configured the FCM with the help of eight clinical psychologists and we investigate the utility of the resulting decision tool using four fictitious scenarios. Results: The current FCM algorithm succeeds in detecting unambiguous risk situations, as well as unambiguously safe situations, but it has more difficulty classifying borderline cases correctly. Based on recommendations from the participants and an analysis of the algorithm's erroneous classifications, we propose how the current FCM algorithm can be further improved. Conclusion: The configuration of FCMs does not necessarily demand large amounts of privacy-sensitive data and their decisions are scrutable. Thus, they hold great potential for automatic decision-making algorithms in mental eHealth. Nevertheless, we conclude that there is a need for clear guidelines and best practices for developing FCMs, specifically for eMental health.</p

Multidisciplinary perspectives on Artificial Intelligence and the law

This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

Ethical Considerations of Chatbot Use for Mental Health Support

The promise of artificial intelligence thus far is greater than its actual application in healthcare, though it has been developed to be used effectively in this field. One application of technology in this setting is chatbot use for mental health support. Chatbots are conversational entities that mimic human conversations to interact with a human user as if two human agents are engaging with one another. Chatbots have the potential to engage those who might otherwise be unable or unwilling to receive mental health care by circumventing many of the barriers that prevent people from receiving care from a human provider. In the mental health arena, both practical barriers (such as geographic location and financial costs) as well as societal barriers (such as self and societal stigma) prevent people from accessing treatment. Even some of those who are able to overcome some most commonly cited barriers to care cannot receive it due to the lack of providers as compared to demand for aid. Thus, there is a need for a massive enhancement of mental health services that is not currently being met, where chatbots could rise to meet these needs. Despite lengthy discussion of the negative possibilities that I will summarize in this paper, the positive outcomes remain especially promising. This technology as a therapy, however, is investigational, as it has not yet been approved for use. Because of this, I advocate for moving forward with this technology, but cautiously. In this paper I will identify different areas of ethical concern regarding chatbot use for mental health support. I will explain why the identification of harms matter, and what steps, if any, can be taken to prevent and mitigate them. Most importantly, I will reiterate that though this technology is investigational thus far, it has the potential to be a widely successful therapeutic solution to many barriers of access, and that these considerations are paramount for the ethical development of this technology in the mental health space

Machine Medical Ethics

In medical settings, machines are in close proximity with human beings: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. Machines in these contexts are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for empathy and emotion detection necessary? What about consciousness? The essays in this collection by researchers from both humanities and science describe various theoretical and experimental approaches to adding medical ethics to a machine, what design features are necessary in order to achieve this, philosophical and practical questions concerning justice, rights, decision-making and responsibility, and accurately modeling essential physician-machine-patient relationships. This collection is the first book to address these 21st-century concerns